FAT* is an international and interdisciplinary peer-reviewed conference that seeks to publish and present work examining the fairness, accountability, and transparency of algorithmic systems. The FAT* conference solicits work from a wide variety of disciplines, including computer science, statistics, the humanities, and law. It intends to bring together the community that has grown through a number of workshops at other conferences, including FATML at NIPS, ICML, and KDD; FATREC at RecSys; Ethics in NLP at EACL, Machine Learning and the Law at NIPS; the Workshop on Data and Algorithmic Bias at CIKM; the Workshop on Discrimination and Privacy-Aware Data Mining at ICDM; Workshop on Human Interpretability at ICML; and the Workshop on Data and Algorithmic Transparency.

To ensure that all submissions to FAT* are reviewed by a knowledgable and appropriate set of reviewers, the conference is divided into tracks with separate track chairs: